As people are becoming interested in paintings, various user-interactive search systems have been presented in recent times. Many systems encourage users to search paintings by prior knowledge on paintings. We discover the limitation for existing methods on how well the query is represented by the user, and propose a simple, yet effective way to search the painting by exploiting the color to express human visual memory. To achieve our goal, we suggest color clustering based on human color perception, and hierarchical metric learning to accommodate the locality of colors. With user-interactive drawing through learned colors, the user completes the abstract image to resemble the visual memory. We show that our system is easy to use, fast to process, accurate to search and fully extensible to cover deviation among users.
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|저 자||Namil Kim, Yukyung Choi, Soonmin Hwang, In So Kweon|
|학 회||International Conference on Image Processing (ICIP)|
|Notes||This work was supported by the Technology Innovation Program (No. 10048320), funded by the Ministry of Trade, Industry & Energy (MI, Korea).|
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